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1d56022
Add maxpool f32 kernel and example
rocking5566 Jun 1, 2023
afe8dae
Revise copyright
rocking5566 Jun 2, 2023
acd980f
Add device pool bwd device op
rocking5566 Jun 2, 2023
7f09b8a
Support f16 and bf16
rocking5566 Jun 6, 2023
85b2fee
Add compute datatype for reference code.
rocking5566 Jun 6, 2023
1737b08
Fix type error
rocking5566 Jun 7, 2023
1a1059a
Remove layout
rocking5566 Jun 8, 2023
81caa44
Fix bf16 error
rocking5566 Jun 8, 2023
b3bc666
Add f16 and bf16 example
rocking5566 Jun 8, 2023
e279b40
Add more operations
rocking5566 Jun 8, 2023
cf9114f
Implement IsSupportedArgument
rocking5566 Jun 8, 2023
3ef4dc7
Add changelog
rocking5566 Jun 9, 2023
8c2c111
Merge branch 'develop' into max-pool-bwd
rocking5566 Jun 9, 2023
e9ca131
Merge branch 'max-pool-bwd' of github.com:ROCmSoftwarePlatform/compos…
rocking5566 Jun 9, 2023
4726df7
Add comment
rocking5566 Jun 15, 2023
9e7cca9
Add comment
rocking5566 Jun 15, 2023
4f1dbdf
Remove useless header
rocking5566 Jun 15, 2023
a2598b8
Move initialize of workspace to the run
rocking5566 Jun 15, 2023
283f9b6
Move set din zero to the device operator
rocking5566 Jun 15, 2023
47ac376
Save din_length_raw
rocking5566 Jun 15, 2023
508d7a5
Remove useless header
rocking5566 Jun 15, 2023
3550cef
Merge branch 'develop' into max-pool-bwd
rocking5566 Jun 15, 2023
38962b9
Calculate gridsize according to the number of CU
rocking5566 Jun 15, 2023
ed4912f
Calculate gridSize according to the number of CU.
rocking5566 Jun 16, 2023
0bf5750
Add put example
rocking5566 Jun 16, 2023
eac452a
Remove useless header
rocking5566 Jun 16, 2023
2720725
Fix CI fail
rocking5566 Jun 16, 2023
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2 changes: 2 additions & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,8 @@ Full documentation for Composable Kernel is not yet available.
- Added multi-embeddings support (#542).
- Added Navi3x blockwise GEMM and real GEMM support (#541).
- Added Navi grouped ConvBwdWeight support (#505).
- Added pool3d forward (#697).
- Added maxpool backward (#750).

### Changed
- Changed ...
3 changes: 3 additions & 0 deletions example/49_maxpool2d_bwd/CMakeLists.txt
Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
add_example_executable(example_maxpool2d_bwd_bf16 maxpool2d_bwd_bf16.cpp)
add_example_executable(example_maxpool2d_bwd_fp16 maxpool2d_bwd_fp16.cpp)
add_example_executable(example_maxpool2d_bwd_fp32 maxpool2d_bwd_fp32.cpp)
62 changes: 62 additions & 0 deletions example/49_maxpool2d_bwd/maxpool2d_bwd_bf16.cpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,62 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.

#include <iostream>

#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/utility/reduction_enums.hpp"

#include "maxpool2d_bwd_common.hpp"

using InDataType = ck::bhalf_t;
using OutDataType = ck::bhalf_t;
using IndexDataType = int32_t;
using ComputeDataType = float;
using DInDataType = ck::bhalf_t;
using DOutDataType = ck::bhalf_t;

static constexpr bool PropagateNan = false;

int main()
{
bool do_verification = true;
bool time_kernel = false;

// Pool shape
ck::index_t N = 1;
ck::index_t C = 1;
ck::index_t Y = 3;
ck::index_t X = 3;
ck::index_t Hi = 32;
ck::index_t Wi = 32;
ck::index_t window_stride_h = 1;
ck::index_t window_stride_w = 1;
ck::index_t in_left_pad_h = 0;
ck::index_t in_left_pad_w = 0;
ck::index_t in_right_pad_h = 0;
ck::index_t in_right_pad_w = 0;

bool pass = maxpool_bwd_test<InDataType,
OutDataType,
IndexDataType,
ComputeDataType,
DInDataType,
DOutDataType,
PropagateNan>(do_verification,
time_kernel,
N,
C,
Y,
X,
Hi,
Wi,
window_stride_h,
window_stride_w,
in_left_pad_h,
in_left_pad_w,
in_right_pad_h,
in_right_pad_w);

return (pass ? 0 : 1);
}
222 changes: 222 additions & 0 deletions example/49_maxpool2d_bwd/maxpool2d_bwd_common.hpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,222 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.

#pragma once

#include <iostream>

#include "ck/ck.hpp"
#include "ck/utility/reduction_enums.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_pool2d_fwd_nhwc_nhwc.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_index_pool_bwd_impl.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
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#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/device_memory.hpp"
#include "ck/library/utility/host_tensor.hpp"
#include "ck/library/utility/host_tensor_generator.hpp"
#include "ck/library/utility/literals.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_pool_fwd.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_maxpool_bwd.hpp"

template <typename InDataType,
typename OutDataType,
typename IndexDataType,
typename ComputeDataType,
typename DInDataType,
typename DOutDataType,
bool PropagateNan>
bool maxpool_bwd_test(bool do_verification,
bool time_kernel,
ck::index_t N,
ck::index_t C,
ck::index_t Y,
ck::index_t X,
ck::index_t Hi,
ck::index_t Wi,
ck::index_t window_stride_h,
ck::index_t window_stride_w,
ck::index_t in_left_pad_h,
ck::index_t in_left_pad_w,
ck::index_t in_right_pad_h,
ck::index_t in_right_pad_w)
{
using PassThrough = ck::tensor_operation::element_wise::PassThrough;

using DevicePoolFwdInstance =
ck::tensor_operation::device::DevicePool2dFwd_Input_N_Hi_Wi_C_Output_N_Ho_Wo_C<
InDataType, // InDataType
OutDataType, // OutDataType
IndexDataType, // IndexDataType
ComputeDataType, // ComputeDataType
ck::ReduceTensorOp::MAX,
true, // OutputIndex
64, // BlockSize
64, // ReduceMThreadClusterSize
1, // ReduceKThreadClusterSize
4, // ReduceMThreadSliceSize
1, // ReduceKThreadSliceSize
1>; // InSrcOutDstVectorSize

using DeviceMaxPoolBwdInstance = ck::tensor_operation::device::
DeviceIndexPoolBwdImpl<DOutDataType, IndexDataType, DInDataType, 4>;

const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - Y) / window_stride_h + 1;
const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - X) / window_stride_w + 1;

const std::vector<ck::index_t> window_spatial_lengths{Y, X};
const std::vector<ck::index_t> window_strides{window_stride_h, window_stride_w};
const std::vector<ck::index_t> input_left_pads{in_left_pad_h, in_left_pad_w};
const std::vector<ck::index_t> input_right_pads{in_right_pad_h, in_right_pad_w};

auto f_host_tensor_descriptor =
[](std::size_t N_, std::size_t C_, std::size_t H, std::size_t W) {
using namespace ck::literals;
// reference need Tensor with NCHW order
return HostTensorDescriptor({N_, C_, H, W}, {C_ * H * W, 1_uz, W * C_, C_});
};

// in
Tensor<InDataType> in_n_c_hi_wi(f_host_tensor_descriptor(N, C, Hi, Wi));

// out
Tensor<OutDataType> out_n_c_ho_wo_host(f_host_tensor_descriptor(N, C, Ho, Wo));
Tensor<OutDataType> out_n_c_ho_wo_device(f_host_tensor_descriptor(N, C, Ho, Wo));

// indices
Tensor<IndexDataType> indices_n_c_ho_wo_device(f_host_tensor_descriptor(N, C, Ho, Wo));
Tensor<IndexDataType> indices_n_c_ho_wo_host(f_host_tensor_descriptor(N, C, Ho, Wo));

// dout
Tensor<DOutDataType> dout_n_c_ho_wo(f_host_tensor_descriptor(N, C, Ho, Wo));

// din
Tensor<DInDataType> din_n_c_hi_wi_host(f_host_tensor_descriptor(N, C, Hi, Wi));
Tensor<DInDataType> din_n_c_hi_wi_device(f_host_tensor_descriptor(N, C, Hi, Wi));

std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi.mDesc << std::endl;
std::cout << "out_n_c_ho_wo: " << out_n_c_ho_wo_host.mDesc << std::endl;
std::cout << "indices_n_c_ho_wo: " << indices_n_c_ho_wo_host.mDesc << std::endl;
std::cout << "dout_n_c_ho_wo: " << dout_n_c_ho_wo.mDesc << std::endl;
std::cout << "din_n_c_hi_wi: " << din_n_c_hi_wi_host.mDesc << std::endl;

in_n_c_hi_wi.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
dout_n_c_ho_wo.GenerateTensorValue(GeneratorTensor_3<DOutDataType>{-1.0, 1.0});

DeviceMem in_device_buf(sizeof(InDataType) * in_n_c_hi_wi.mDesc.GetElementSpaceSize());
DeviceMem out_device_buf(sizeof(OutDataType) *
out_n_c_ho_wo_device.mDesc.GetElementSpaceSize());
DeviceMem indices_device_buf(sizeof(IndexDataType) *
indices_n_c_ho_wo_device.mDesc.GetElementSpaceSize());
DeviceMem dout_device_buf(sizeof(DOutDataType) * dout_n_c_ho_wo.mDesc.GetElementSpaceSize());
DeviceMem din_device_buf(sizeof(DInDataType) *
din_n_c_hi_wi_device.mDesc.GetElementSpaceSize());

in_device_buf.ToDevice(in_n_c_hi_wi.mData.data());
dout_device_buf.ToDevice(dout_n_c_ho_wo.mData.data());

auto pool_fwd = DevicePoolFwdInstance{};
auto pool_fwd_invoker_ptr = pool_fwd.MakeInvokerPointer();
auto pool_fwd_argument_ptr = pool_fwd.MakeArgumentPointer(
static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),
static_cast<OutDataType*>(out_device_buf.GetDeviceBuffer()),
static_cast<IndexDataType*>(indices_device_buf.GetDeviceBuffer()),
{N, C, Hi, Wi},
window_spatial_lengths,
{N, C, Ho, Wo},
{C * Hi * Wi, 1, Wi * C, C},
{C * Ho * Wo, 1, Wo * C, C},
{C * Ho * Wo, 1, Wo * C, C},
window_strides,
input_left_pads,
input_right_pads,
{2, 3});

if(!pool_fwd.IsSupportedArgument(pool_fwd_argument_ptr.get()))
{
throw std::runtime_error("wrong! pool_fwd with the specified compilation parameters does "
"not support this problem");
}

float ave_time_fwd =
pool_fwd_invoker_ptr->Run(pool_fwd_argument_ptr.get(), StreamConfig{nullptr, time_kernel});

auto pool_bwd = DeviceMaxPoolBwdInstance{};
auto pool_bwd_invoker_ptr = pool_bwd.MakeInvokerPointer();
auto pool_bwd_argument_ptr = pool_bwd.MakeArgumentPointer(
static_cast<DOutDataType*>(dout_device_buf.GetDeviceBuffer()),
static_cast<IndexDataType*>(indices_device_buf.GetDeviceBuffer()),
static_cast<DInDataType*>(din_device_buf.GetDeviceBuffer()),
dout_n_c_ho_wo.mDesc.GetElementSpaceSize(),
din_n_c_hi_wi_device.mDesc.GetElementSpaceSize(),
window_spatial_lengths,
window_strides);

if(!pool_bwd.IsSupportedArgument(pool_bwd_argument_ptr.get()))
{
throw std::runtime_error("wrong! pool_bwd with the specified compilation parameters does "
"not support this problem");
}

size_t pool_bwd_workspace_sz = pool_bwd.GetWorkSpaceSize(pool_bwd_argument_ptr.get());
DeviceMem pool_bwd_workspace_device_buf(pool_bwd_workspace_sz);
pool_bwd.SetWorkSpacePointer(pool_bwd_argument_ptr.get(),
pool_bwd_workspace_device_buf.GetDeviceBuffer());

float ave_time_bwd =
pool_bwd_invoker_ptr->Run(pool_bwd_argument_ptr.get(), StreamConfig{nullptr, time_kernel});

std::cout << "Pool fwd perf: " << ave_time_fwd << " ms" << std::endl;
std::cout << "Pool bwd perf: " << ave_time_bwd << " ms" << std::endl;

bool pass = true;

if(do_verification)
{
using ReferencePoolingFwdInstance =
ck::tensor_operation::host::ReferencePoolingFwd<4,
2,
InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::ReduceTensorOp::MAX,
PropagateNan,
true>;

auto ref_pooling_fwd = ReferencePoolingFwdInstance{};
auto ref_pooling_fwd_invoker = ref_pooling_fwd.MakeInvoker();
auto ref_pooling_fwd_argument = ref_pooling_fwd.MakeArgument(in_n_c_hi_wi,
out_n_c_ho_wo_host,
indices_n_c_ho_wo_host,
window_spatial_lengths,
window_strides,
input_left_pads,
input_right_pads);
ref_pooling_fwd_invoker.Run(ref_pooling_fwd_argument);

using ReferencePoolingBwdInstance =
ck::tensor_operation::host::ReferenceMaxPoolBwd<DOutDataType,
IndexDataType,
ComputeDataType,
DInDataType,
PassThrough>;

auto ref_pooling_bwd = ReferencePoolingBwdInstance{};
auto ref_pooling_bwd_invoker = ref_pooling_bwd.MakeInvoker();
auto ref_pooling_bwd_argument = ref_pooling_bwd.MakeArgument(
dout_n_c_ho_wo, indices_n_c_ho_wo_host, din_n_c_hi_wi_host, PassThrough{});

ref_pooling_bwd_invoker.Run(ref_pooling_bwd_argument);

out_device_buf.FromDevice(out_n_c_ho_wo_device.mData.data());
indices_device_buf.FromDevice(indices_n_c_ho_wo_device.mData.data());
din_device_buf.FromDevice(din_n_c_hi_wi_device.mData.data());

pass = pass && ck::utils::check_err(out_n_c_ho_wo_device, out_n_c_ho_wo_host);
pass = pass && ck::utils::check_err(indices_n_c_ho_wo_device, indices_n_c_ho_wo_host);
pass = pass && ck::utils::check_err(din_n_c_hi_wi_device, din_n_c_hi_wi_host);
}

return (pass);
};
62 changes: 62 additions & 0 deletions example/49_maxpool2d_bwd/maxpool2d_bwd_fp16.cpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,62 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.

#include <iostream>

#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/utility/reduction_enums.hpp"

#include "maxpool2d_bwd_common.hpp"

using InDataType = ck::half_t;
using OutDataType = ck::half_t;
using IndexDataType = int32_t;
using ComputeDataType = float;
using DInDataType = ck::half_t;
using DOutDataType = ck::half_t;

static constexpr bool PropagateNan = false;

int main()
{
bool do_verification = true;
bool time_kernel = false;

// Pool shape
ck::index_t N = 1;
ck::index_t C = 1;
ck::index_t Y = 3;
ck::index_t X = 3;
ck::index_t Hi = 32;
ck::index_t Wi = 32;
ck::index_t window_stride_h = 1;
ck::index_t window_stride_w = 1;
ck::index_t in_left_pad_h = 0;
ck::index_t in_left_pad_w = 0;
ck::index_t in_right_pad_h = 0;
ck::index_t in_right_pad_w = 0;

bool pass = maxpool_bwd_test<InDataType,
OutDataType,
IndexDataType,
ComputeDataType,
DInDataType,
DOutDataType,
PropagateNan>(do_verification,
time_kernel,
N,
C,
Y,
X,
Hi,
Wi,
window_stride_h,
window_stride_w,
in_left_pad_h,
in_left_pad_w,
in_right_pad_h,
in_right_pad_w);

return (pass ? 0 : 1);
}
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